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The goal of the proposed method is to discover genes as biomarkers that have similar expression profiles in time-series conditions and are also significantly ...
In this paper, we propose a novel gene clustering method named TGmix through integrated analysis on two types of datasets, namely the time-series and twogroup ...
In this paper, we propose a novel gene clustering method named TGmix through integrated analysis on two types of datasets, namely the time-series and ...
Discovering Gene Clusters via Integrated Analysis on Time-Series and Group-Comparative Microarray Datasets. Resource URI: https://dblp.l3s.de/d2r/resource ...
Gene expression profiles based on microarray data have been suggested by many studies as potential molecular prognostic indexes of breast cancer.
Oct 22, 2024 · A challenging task in time series microarray data analysis is to identify co-expressed groups of genes from a large input space.
Time-series microarray experiments have far greater applications than static experiments [4]. First, it is utilized in the discovery of the dynamics behind.
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Clustering time-varying gene expression profiles using scale-space signals.. ... Evaluation and comparison of gene clustering methods in microarray analysis.
Missing: via | Show results with:via
Traditional clustering methods have been applied to the analysis of microarray time course data (Lukashin and Fuchs, 2001; Spellman et al., 1998) and more ...
Missing: Integrated | Show results with:Integrated
Jun 29, 2009 · We propose to analyse copy number and expression array data using gene sets, rather than individual genes. The proposed model is robust and ...